Data Pitch is an EU-funded open innovation programme that brings together business and public sector organizations with startups and SMEs. Promoting organizations provide data and launch challenges and startups work that data in order to overcome those challenges. The programme includes a virtual acceleration programme (6 months) to support startups and SMEs in the process of developing solutions.
The Data Pitch is coordinated by the portuguese Beta-I accelerator, together with the University of Southampton, the Open Data Institute and the french Dawex data platform.
Altice Labs is one of the promoters, in partnership with Beta-i, and has already identified two challenges in the area of IPTV, supported by anonymized data visualization content on the MEO platform.
The 1st challenge, which will be taken over by the Utelly startup, is focused on customizing linear TV consumption. With the advent of Subscription Video On Demand (SVOD) platforms, content recommendation processes have evolved considerably, but their transposition into linear TV scenarios with Automatic Recordings (such as those offered by the MEO service) have come up against the specificities of this service, limiting the effectiveness of existing recommendation processes. In this sense, it is intend to implement a recommendation solution that, based on the identification of consumption patterns by time period (thus distinguishing which family element may be using the TV), consider the intrinsic characteristics of the programmes (football matches are different from news programmes which in turn differ from movies …), be proactive in suggesting recommendations (eg zapping situations, after the end of the programme, …) and have a retrospective view of content consumption (in order to allow viewing scenarios and blur the line between linear TV and TV on demand concepts).
The 2nd challenge, which will be taken by holler.live startup, is centered on the context transference of TV to mobile equipment. It intends to explore and enhance the use of mobile equipment in the TV ecosystem, allowing to offer a set of complementary services that add value to the TV consumption experience. The goal will be to develop a platform where the customer can be notified on TV, the existence of an opportunity for interaction (eg betting on a game being watched, offering product coupons in a geographically nearby store) that can be executed through a mobile device, with greater flexibility and usability. In this case, the visualization data processing is intended for the creation of usage profiles that allow better adaptation of interaction opportunities notifications to each user, in order to be as assertive as possible in the notifications sent to each user.